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公开(公告)号：US10949658B2
公开(公告)日：2021-03-16
申请号：US16276493
申请日：2019-02-14
申请人： WRNCH Inc.
发明人： Colin J. Brown , Andrey Tolstikhin , Thomas D. Peters , Dongwook Cho , Maggie Zhang , Paul A. Kruszewski
摘要： This disclosure is directed to an activity classifier system, for classifying human activities using 2D skeleton data. The system includes a skeleton preprocessor that transforms the 2D skeleton data into transformed skeleton data, the transformed skeleton data comprising scaled, relative joint positions and relative joint velocities. It also includes a gesture classifier comprising a first recurrent neural network that receives the transformed skeleton data, and is trained to identify the most probable of a plurality of gestures. There is also an action classifier comprising a second recurrent neural network that receives information from the first recurrent neural networks and is trained to identify the most probable of a plurality of actions.
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公开(公告)号：US20210264144A1
公开(公告)日：2021-08-26
申请号：US17256307
申请日：2019-06-27
申请人： WRNCH INC.
发明人： Dongwook Cho , Maggie Zhang , Paul Kruszewski
摘要： System and method for extracting human pose information from an image, comprising a feature extractor connected to a database, a convolutional neural network (CNN) with a plurality of CNN layers. Said system/method further comprising at least one of the following modules: a 2D body skeleton detector for determining 2D body skeleton information from the human-related image features; a body silhouette detector for determining body silhouette information from the human-related image features; a hand silhouette detector for determining hand silhouette detector from the human-related image features; a hand skeleton detector for determining hand skeleton from the human-related image features; a 3D body skeleton detector for determining 3D body skeleton from the human-related image features; and a facial keypoints detector for determining facial keypoints from the human-related image features.
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公开(公告)号：US20210161266A1
公开(公告)日：2021-06-03
申请号：US17173978
申请日：2021-02-11
申请人： WRNCH INC.
发明人： Colin J. Brown , Andrey Tolstikhin , Thomas D. Peters , Dongwook Cho , Maggie Zhang , Paul A. Kruszewski
摘要： An activity classifier system and method that classifies human activities using 2D skeleton data. The system includes a skeleton preprocessor that transforms the 2D skeleton data into transformed skeleton data, the transformed skeleton data comprising scaled, relative joint positions and relative joint velocities. The system also includes a gesture classifier comprising a first recurrent neural network that receives the transformed skeleton data, and is trained to identify the most probable of a plurality of gestures. The system also has an action classifier comprising a second recurrent neural network that receives information from the first recurrent neural networks and is trained to identify the most probable of a plurality of actions.
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公开(公告)号：US20190251340A1
公开(公告)日：2019-08-15
申请号：US16276493
申请日：2019-02-14
申请人： WRNCH Inc.
发明人： Colin J. Brown , Andrey Tolstikhin , Thomas D. Peters , Dongwook Cho , Maggie Zhan , Paul A. Kruszewski
CPC分类号： G06K9/00342 , G06K9/00208 , G06N3/0454 , G06N3/08
摘要： This disclosure is directed to an activity classifier system, for classifying human activities using 2D skeleton data. The system includes a skeleton preprocessor that transforms the 2D skeleton data into transformed skeleton data, the transformed skeleton data comprising scaled, relative joint positions and relative joint velocities. It also includes a gesture classifier comprising a first recurrent neural network that receives the transformed skeleton data, and is trained to identify the most probable of a plurality of gestures. There is also an action classifier comprising a second recurrent neural network that receives information from the first recurrent neural networks and is trained to identify the most probable of a plurality of actions.
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